In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for differ

         The world's population growth and the increasing demand for new infrastructure facilities and buildings , present us with the vision of a higher resources consumption, specially in the form of more durable concrete such as High Performance Concrete (HPC) . Moreover , the growth of the world pollution by plastic waste has been tremendous. The aim of this research is to investigate the change in mechanical properties of HPC with added waste plastics in concrete. For this purpose 2.5%, 5% and 7.5% in volume of natural fine aggregate in the HPC mixes were replaced by an equal volume of Polyethylene Terephthalate (PET) waste , got by shredded PET bottles. The mechanical propert

اعداد : أسرار عبد الزهراء علي - علاء الدين - ب. جواد  حسن عودة عبد الله  - جامعة بغداد جامعة بغداد كلية البصرة للعلوم والتكنولوجيا - كلية الإدارة والاقتصاد. كلية الإدارة والاقتصاد المركز الديمقراطي العربي –   مجلة القانون الدستوري والعلوم الإدارية : العدد التاسع شباط – فبراير 2021 المجلد 3 ،

The sensors based on Nickel oxide doped chromic oxide (NiO: Cr2O3) nanoparticals were fabricated using thick-film screen printing of sol-gel grown powders. The structural, morphological investigations were carried out using XRD, AFM, and FESEM. Furthermore, the gas responsivity were evaluated towards the NH3 and NO2 gas. The NiO0.10: Cr2O3 nanoparticles exhibited excellent response of 95 % at 100oC and better selectivity towards NH3 with low response and recovery time as compared to pure Cr2O3 and can stand as reliable sensor element for NH3 sensor related applications.

Based on the diazotization-coupling reaction, a new, simple, and sensitive spectrophotometric method for determining of a trace amount of (BPF) is presented in this paper. Diazotized metoclopramide reagent react with bisphenol F produces an orange azo-compound with a maximum absorbance at 461 nm in alkaline solution. The experimental parameters were optimized such as type of alkaline medium, concentration of NaOH, diazotized metoclopramide amount, order additions, reaction time, temperature, and effect of organic solvents to achieve the optimal performance for the proposed method. The absorbance increased linearly with increasing bisphenol F concentration in the range of 0.5-10 μg mL^-1 under ideal conditions, with a correlati